Modern electric utility companies are confronted with various economic, regulatory, and environmentally related pressures which complicate, and sometimes prevent, construction of more generating capacity in response to market or service territory growth. As a consequence, although such companies usually give considerable attention to programs for energy conservation so as to moderate demand and thereby offset need for increased generating capacity, thought is currently being given by utilities to various strategies or techniques for managing or regulating customer demand for electric energy. The objective of such strategies from the utility point of view is to moderate the peaks and valleys of fluctuations in electric energy use over a given time frame such as a twenty-four hour day, and thereby smooth out the demand level over such a time period. This enables generating capacity already in place to be used most efficiently.
Electric energy users in turn have economic incentives to minimize the cost of their energy demands. Attention has therefore been focused from both supply side and demand side on efforts to achieve both reduced fluctuations in demand required to be met by the supplier, and derivation from such reduced fluctuations of lower costs for the user.
Prior art demand side management efforts on the part of utilities have involved such techniques as time-of-use pricing, in which prices are lowered to encourage filling of demand valleys and raised to moderate customer demand at peak hours, and automated shut-off of selected customer equipment such as water heaters during peak demand hours. Temporary shedding of loads in a rolling fashion in a given market or service territory is another known technique for moderating peak demand.
Unfortunately, in the aforementioned prior art systems, the user is required to provide certain startup information. For example, upon initial installation, the user is expected to provide the building design load and building use schedules, startup values for cooling load profile, noncooling electric load profile, and ambient temperature profile. Also, the user must provide maximum ton-hours of storage compacity, maximum chiller cooling rate, and maximum storage discharge rate in tons.
Such prior art techniques have lacked the sophistication required for timely consideration of all significant user-related parameters such as prospective next-day heating or cooling requirements or machine run time. They also lack the ability to respond promptly to changes in significant supplier-related factors such as variations in generating costs. Moreover, such prior art techniques rely on the user to provide a great number of initial parameters and design characteristics, which may or may not be reliable and are certainly inconvenient for the user to enter into the system periodically.
It would be advantageous and is, in fact, one of the objects of the present invention, to provide a dynamic adaptive energy scheduling system that will allow variations in parameters, transparent to the user. In the course of operating the present system of the invention, certain parameters are obtained, but need not be expressly entered into the system by the operator.
Prior art systems may also require a user to specifically provide the high and low ambient temperatures predicted by the National Weather Service for the next day. Once again, the use of a non-automated system for providing this information and the lack of updating such information has resulted in a serious impediment to the use of such systems. The fact is, that few operators take the time necessary to input this information on a daily basis and, even when they do, the information can become outdated rapidly as weather conditions change during the day. Thus, it would be advantageous to provide an energy scheduling system that calculates and recalculates predictive weather information on the basis of ongoing, changing data acquired by the system automatically and periodically.